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Long-range plan for meeting mental health, developmental disabilities & substance abuse services needs for the State of North Carolina

Heart of the Matter, Inc & Pareto Solutions, LLC 12/ 14/ 2006 Page149 of 172
Interrelationships of Cost Variables
Since population is also increasing each year, we calculated costs as an average
monthly cost per capita, ( i. e. per citizen in the population. In addition to increasing costs
for community- based services, we examined the impact of assumed increases in
treated prevalence among categories of consumers with especially low treated
prevalence and in counties with below average rates of treated prevalence. These
increases in treated prevalence were limited to affordable levels while maintaining
reasonable continuity, ( recall that increasing prevalence without increasing average
monthly caseload will result in a reduction in continuity for those being served). There
were only slight projected increases in the treated prevalence of developmental
disabilities and SED to maintain them at their current level given population increases,
and stronger increases in the rate for SA and Adult SMI.
Improvements in continuity must also be gained at the same time one is increasing
treated prevalence. Based on assumed increases in both total persons served annually
and the average monthly caseload, we introduced major gains in continuity over the
initial draft of this Analysis. This has the effect of increasing costs dramatically.
As population increases, we forecasted a relatively greater use of EBP services, an
increase in treated prevalence, to bring NC up to the national average, while realizing
major gains in average continuity of care.
Benefit Model
The Defined Benefit Model is intended to estimate costs for those non- Medicaid eligible
persons that require services from the public system. Only 14% of the recipients are
insured by Medicaid. The State desires keeping EBPs for this group to maintain a
smooth transition for the consumer to Medicaid services ( if and when eligible) and to
offer a benefit as close to the Medicaid benefit as possible to facilitate good quality care
and prevent State Facility use. The more usual ways that benefits are reduced to save
are to reduce the number of different services offered ( i. e. reduce scope of benefits), or
to reduce the total amount of service that an eligible person can receive. None of these
appeared to be acceptable alternatives in our discussions with the Division leadership
staffs.
That decision essentially leaves the only other alternative, which is to alter the
requirements for eligibility for services. The State has established “ Target Populations”
to be served. In examining the treated prevalence data by county, it is apparent that
many LMEs are serving people who may not meet these Target Population criteria
because their rate of treated prevalence is too high. What that means is the LME is
serving people with mental health problems, and not just those with the most severe
conditions. By evaluating each county’s treated prevalence and reducing the treated
prevalence in counties that were outliers we were able to establish a basis for significant
Final

Heart of the Matter, Inc & Pareto Solutions, LLC 12/ 14/ 2006 Page149 of 172
Interrelationships of Cost Variables
Since population is also increasing each year, we calculated costs as an average
monthly cost per capita, ( i. e. per citizen in the population. In addition to increasing costs
for community- based services, we examined the impact of assumed increases in
treated prevalence among categories of consumers with especially low treated
prevalence and in counties with below average rates of treated prevalence. These
increases in treated prevalence were limited to affordable levels while maintaining
reasonable continuity, ( recall that increasing prevalence without increasing average
monthly caseload will result in a reduction in continuity for those being served). There
were only slight projected increases in the treated prevalence of developmental
disabilities and SED to maintain them at their current level given population increases,
and stronger increases in the rate for SA and Adult SMI.
Improvements in continuity must also be gained at the same time one is increasing
treated prevalence. Based on assumed increases in both total persons served annually
and the average monthly caseload, we introduced major gains in continuity over the
initial draft of this Analysis. This has the effect of increasing costs dramatically.
As population increases, we forecasted a relatively greater use of EBP services, an
increase in treated prevalence, to bring NC up to the national average, while realizing
major gains in average continuity of care.
Benefit Model
The Defined Benefit Model is intended to estimate costs for those non- Medicaid eligible
persons that require services from the public system. Only 14% of the recipients are
insured by Medicaid. The State desires keeping EBPs for this group to maintain a
smooth transition for the consumer to Medicaid services ( if and when eligible) and to
offer a benefit as close to the Medicaid benefit as possible to facilitate good quality care
and prevent State Facility use. The more usual ways that benefits are reduced to save
are to reduce the number of different services offered ( i. e. reduce scope of benefits), or
to reduce the total amount of service that an eligible person can receive. None of these
appeared to be acceptable alternatives in our discussions with the Division leadership
staffs.
That decision essentially leaves the only other alternative, which is to alter the
requirements for eligibility for services. The State has established “ Target Populations”
to be served. In examining the treated prevalence data by county, it is apparent that
many LMEs are serving people who may not meet these Target Population criteria
because their rate of treated prevalence is too high. What that means is the LME is
serving people with mental health problems, and not just those with the most severe
conditions. By evaluating each county’s treated prevalence and reducing the treated
prevalence in counties that were outliers we were able to establish a basis for significant
Final